1. Field of the Invention
This invention relates generally to methods that improve the accuracy of gene expression profiling, and more particularly to methods for quantitative PCR (QPCR) used to determine the level of gene expression or gene copy number in a high-throughput fashion.
2. Description of the Related Art
The ability to monitor the real-time progress of the Polymerase Chain Reaction (PCR) has revolutionized the way one approaches quantification of DNA and RNA. A real-time quantitative PCR (QPCR) assay provides a large dynamic range of detection and a highly sensitive method for determining the amount of DNA template of interest. When QPCR follows a reverse transcription reaction, it can be used to quantify RNA templates as well. QPCR makes quantification of DNA and RNA much more precise and reproducible because it relies on the analysis of PCR kinetics rather than endpoint measurements.
The determination of DNA or RNA levels of biological samples in a high throughput fashion has been made possible by the QPCR instrument. Commercially available QPCR instruments, and related data acquisition and analysis software, process QPCR assay data generated from biological samples. These systems report quantitative results by calculating a threshold cycle (CT) value as the fractional PCR cycle number where the reporter signal rises above a threshold set manually by a human or automatically by software. The precision and reproducibility of the quantitative result for gene expression depends on the accuracy of this CT value.
FIG. 1 illustrates a typical 40 cycle amplification graph generated by a QPCR analysis system. When the data is displayed in a logarithmic plot of reporter signal vs. cycle number (FIG. 2), a typical amplification curve manifests four distinct phases that characterize the progression of the PCR reaction. These four phases can be termed as Initial Phase, Geometric Phase, Linear Phase, and Plateau Phase.
The initial phase is characterized by a low level amplification signal within the background noise of the assay. The initial phase begins at the first cycle and ends prior to the beginning of the geometric phase.
The geometric phase is characterized by high and constant amplification efficiency. It may also be referred to as the exponential amplification phase, or log phase. The geometric phase begins at the first detectable rise in reporter signal above background and ends prior to the beginning of the linear phase. When plotted on a log scale of signal vs. cycle number, the curve generated by the geometric phase should approximate a straight line with a slope. A commercial QPCR instrument typically delivers sufficient sensitivity to detect at least 3 cycles in the geometric phase, assuming reasonably optimized PCR conditions.
The linear phase is characterized by a leveling effect where the slope of the amplification curve decreases steadily. At this point, one or more reaction components have fallen below a critical concentration and the amplification efficiency has begun to decrease. This phase is termed linear, because amplification approximates an arithmetic progression, rather than a geometric increase.
Finally, the amplification curve achieves the plateau phase at which time the PCR amplification levels and the reporter signal remains relatively constant.
QPCR instrumentation software is designed to monitor, record, and analyze the real time fluorescent signal data through these phases and then calculate a CT value that can be used to estimate the initial quantity of the DNA templates. Detection of the geometric phase is the key to high-precision CT values and reliable QPCR results. At any given cycle or fractional cycle within the geometric phase the amount of product in theory is proportional to the initial number of template copies.
In a high throughput environment, an erroneous CT value may be reported by software due to several factors including data variation, inefficient amplification, non-specific amplification, and background noise. Such estimation errors may lead to invalid or incomparable assay results.
The limitations of currently available commercial software that may lead to an erroneous quantitation result include the following:
The automatic or manual setting of a threshold for each assay plate may not be appropriate. In order to compare the gene expression levels with accuracy across different patient samples or different genes, the threshold may need to be set as a fixed value in the geometric phase region.
A false CT value due to atypical or low efficiency amplification. For example, a CT value generated an the amplification with a linear rise in the fluorescent signal due to non-specific amplification or probe degradation.
A false reported Ct value due to a PCR cycle “glitch” or instrument measurement error. For example, a non-homogenous reaction condition or transient fluorescent reading can cause the fluorescent signal to rise above threshold as shown in FIG. 10.
An inaccurate reported CT value due to reference signal changes. For example, a decrease in a reference signal, such as ROX, or high variability of background fluorescence may distort the amplification curve and generate an inaccurate CT.
Software algorithms and products that have been surveyed can perform computations in ideal amplification situations but may perform less reliably or generate inaccurate results when an amplification is marginal or poor. In general, they do not have mechanisms to detect errors automatically, and require the user to manually flag or reject invalid results.
There is a need for improved methods and system to analyze and quantify QPCR results. There is a further need to quantify QCPR results to achieve reliable and statistically significant results to profile expression of genes of diagnostic and prognostic importance. There is a further need for automated methods and systems for the quality control and accurate computational analysis of QPCR data. There is yet a further need for improved methods and system to profile the expression of genes with a reduced error rate in a high throughput setting.